Client computing device health-related suggestions

• US 10,678,890 B2
• Filed: 12/16/2015
• Issued: 06/09/2020
• Est. Priority Date: 08/06/2015
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Bitran, Hadas, Holmdahl, Todd, Horvitz, Eric, Tan, Desney S., Schmuland, Dennis Paul, Berns, Adam T., Bilodeau, Brian
• Primary Examiner(s): Tomaszewski, Michael
• Application Number:
  US14/971,702
• Publication Number:
  US 20170039327A1
• Time in Patent Office: 1,637 Days
• Field of Search: None
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/20 relating to practices or guidelines
• CPC Class Codes: H04L 63/0421 Anonymous communication, i.e. the party's identifiers are hidden from the other party or parties, e.g. using an anonymizer
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]

Abstract

A client computing device is disclosed that comprises a processor and an electronic personal assistant application program. The personal assistant application program may be configured to capture user data associated with user activities across a plurality of computer programs. The user data may be sent to a personal assistant user data interpretation engine. A health-related suggestion based on at least a subset of the user data and anonymized statistics of a user population retrieved from an aggregated knowledge base may be received. The health-related suggestion may be displayed on a display associated with the client computing device.

Claims

1. A client computing device for providing a health-related suggestion, comprising:

a processor; and

an electronic personal assistant application program executable by the processor, the personal assistant application program configured to;

capture user data associated with user activities of a user across a plurality of computer programs;

send the user data to a personal assistant user data interpretation engine to determine one or more predetermined context triggers for delivery of the health-related suggestion to the client computing device of the user by application of a machine learning algorithm to the user data;

receive, from a remote computing device over a communications network, the health-related suggestion that is based on at least a subset of the user data and anonymized statistics of a user population retrieved from an aggregated knowledge base, wherein delivery of the health-related suggestion by the remote computing device is triggered by detection of an occurrence of a predetermined context trigger of the one or more predetermined context triggers;

based on the health-related suggestion, generate instructions for controlling an electronic drug delivery device to dispense an adjusted amount of a therapeutic agent, wherein the processor determines the adjusted amount of the therapeutic agent based at least on the anonymized statistics of the user population retrieved from the aggregated knowledge base; and

transmit the instructions to the electronic drug delivery device to dispense the adjusted amount of the therapeutic agent.

2. The client computing device of claim 1, wherein the personal assistant application program is further configured to adjust an exercise setting on an exercise device that is communicatively coupled to the client computing device based on the health-related suggestion.

3. The client computing device of claim 1, wherein the personal assistant application program is further configured to control another medical device that is communicatively coupled to the client computing device based on the health-related suggestion.

4. The client computing device of claim 1, wherein the anonymized statistics of the user population are processed by the machine learning algorithm to apply weightings and rank a plurality of health-related suggestions comprising the health-related suggestion.

5. The client computing device of claim 1, wherein the anonymized statistics of the user population comprise browsing histories of the user population.

6. The client computing device of claim 1, wherein the anonymized statistics of the user population comprise anonymized medical record statistics.

7. The client computing device of claim 1, wherein the anonymized statistics of the user population are based on a predefined cohort of the user population.

8. The client computing device of claim 1, wherein the subset of the user data comprises data from a user electronic medical record.

9. The client computing device of claim 1, wherein the subset of the user data comprises data from a browsing history of the user.

10. The client computing device of claim 1, wherein the personal assistant application program is further configured to:

receive user biometric data from at least one biometric computing device; and

send the user biometric data to the personal assistant user data interpretation engine,

wherein the subset of the user data comprises the user biometric data.

11. A method enacted at a remote computing device for providing a health-related suggestion, comprising:

receiving from a client computing device over a communications network user data associated with user activities of a user across a plurality of computer programs;

retrieving anonymized statistics of a user population from one or more aggregated knowledge bases;

determining the health-related suggestion based on at least a subset of the user data and the anonymized statistics of the user population;

using a machine learning algorithm to determine a predetermined context trigger associated with the user of the client computing device for delivery of the health-related suggestion to the client computing device of the user; and

upon detection of an occurrence of the predetermined context trigger, sending the health-related suggestion to the client computing device, thereby causing the client computing device to;

based on the health-related suggestion, generate instructions for controlling an electronic drug delivery device to dispense an adjusted amount of a therapeutic agent, wherein the adjusted amount of the therapeutic agent is determined based at least on the anonymized statistics of the user population retrieved from the aggregated knowledge base, and

transmit the instructions to the electronic drug delivery device to dispense the adjusted amount of the therapeutic agent.

12. The method of claim 11, further comprising adjusting an exercise setting on an exercise device that is communicatively coupled to the client computing device based on the health-related suggestion.

13. The method of claim 11, further comprising controlling another medical device that is communicatively coupled to the client computing device based on the health-related suggestion.

14. The method of claim 11, further comprising implementing the machine learning algorithm to apply weightings to a plurality of health-related suggestions comprising the health-related suggestion, and to rank the plurality of health-related suggestions according to the weightings.

15. The method of claim 11, wherein the anonymized statistics of the user population comprise browsing histories of the user population.

16. The method of claim 11, wherein the anonymized statistics of the user population comprise anonymized medical record statistics.

17. The method of claim 11, wherein the subset of the user data comprises data from a user electronic medical record.

18. The method of claim 11, wherein the health-related suggestion comprises an event, and the anonymized statistics of the user population comprise one or more of information of past participation in the event by the user population and browsing histories of the user population related to the event.

19. A client computing device for providing a health-related suggestion, comprising:

a processor; and

an electronic personal assistant application program executable by the processor, the personal assistant application program configured to;

capture user data associated with user activities of a user across a plurality of computer programs;

send the user data to a personal assistant user data interpretation engine to determine one or more predetermined context triggers for delivery of the health-related suggestion to the client computing device of the user by application of a machine learning algorithm to the user data;

receive, from a remote computing device over a communications network, the health-related suggestion that is based on at least a subset of the user data and anonymized statistics of a user population retrieved from an aggregated knowledge base, wherein the anonymized statistics of the user population are processed by the machine learning algorithm to apply weightings and rank a plurality of health-related suggestions comprising the health-related suggestion, wherein delivery of the health-related suggestion by the remote computing device is triggered by detection of an occurrence of a predetermined context trigger of the one or more predetermined context triggers;

based on the health-related suggestion, generate instructions for controlling an electronic drug delivery device to dispense an adjusted amount of a therapeutic agent, wherein the processor determines the adjusted amount of the therapeutic agent based at least on the anonymized statistics of the user population retrieved from the aggregated knowledge base; and

transmit the instructions to the electronic drug delivery device to dispense the adjusted amount of the therapeutic agent.